Back to Deploy Models with TensorFlow Serving and Flask
Learner Reviews & Feedback for Deploy Models with TensorFlow Serving and Flask by Coursera Project Network
184 ratings
About the Course
In this 2-hour long project-based course, you will learn how to deploy TensorFlow models using TensorFlow Serving and Docker, and you will create a simple web application with Flask which will serve as an interface to get predictions from the served TensorFlow model.
This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your Internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with (e.g. Python, Jupyter, and Tensorflow) pre-installed.
Prerequisites:
In order to be successful in this project, you should be familiar with Python, TensorFlow, Flask, and HTML.
Notes:
- You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want.
- This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Top reviews
Sep 14, 2020
This course helped me a lot, I was confused and looked up a lot of articles on deploying deep learning models with tensorflow but this one helped by a great margin.
Dec 10, 2020
Excellent! I will rate this as the best rhyme project that I have done so far. The instructor does an excellent job in explaining all the parts.
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